Data Engineer

Your Role

As a Data Engineer, you will design, build, and maintain enterprise data platforms that support AI-driven products and analytics initiatives. You will work closely with Data Scientists, Architects, AI Engineers, and business stakeholders to develop robust data pipelines, digital twin platforms, knowledge graphs, and AI-ready data architectures.

• Design and implement data source connectors for telemetry, topology, intent, ITSM, knowledge repositories, and enterprise applications.
• Build ingestion, validation, replay, and data contract frameworks for large-scale data onboarding.
• Develop ingestion and topology mapping capabilities to transform raw telemetry into incident-aware datasets.
• Design, develop, and maintain Network Digital Twin and topology graph platforms.
• Build and manage Knowledge Graphs, ontology frameworks, entity relationships, and semantic data models.
• Develop reusable Feature Engineering Frameworks and Feature Store capabilities for AI/ML applications.
• Enable data foundations for RAG, GraphRAG, Vector Databases, and AI Agent frameworks.
• Develop and optimize data pipelines for model training, deployment, monitoring, and lifecycle management.
• Implement metadata management, lineage tracking, observability, security, auditing, and governance frameworks.
• Support integrations with AI reasoning engines, recommendation systems, and agent orchestration platforms.
• Collaborate with cross-functional teams to deliver scalable, enterprise-grade AI and analytics solutions.

Your Profile

• Strong programming expertise in Python and SQL.
• Experience with JavaScript, React, or Angular.
• Strong knowledge of Data Modeling, ETL/ELT, and Data Architecture principles.
• Hands-on experience with Apache Spark, Spark Streaming, and Kafka.
• Experience building and managing Data Lakes.
• Strong experience with AWS services including: S3, Glue, Lambda, SageMaker
• Knowledge of Machine Learning, Deep Learning, Predictive Analytics, and Statistical Modeling.
• Experience with Generative AI technologies including: Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG) , AI Agents ,Agentic AI Frameworks
• Expertise in: Relational Databases, Graph Databases , Vector Databases
• Experience building APIs, Data Pipelines, and Batch/Real-Time Data Processing frameworks.
• Strong understanding of: Data Quality , Metadata Management, Data Lineage, Data Governance
• AWS Glue and Azure Data Factory.
• SageMaker Pipelines.
• Experience with Digital Twin platforms and architectures.
• Knowledge of GraphRAG and advanced RAG solutions.
• MLOps and LLMOps implementation experience.
• DataOps practices and automation frameworks.
• Experience with Enterprise Knowledge Management Platforms.
• Strong analytical, debugging, and problem-solving skills.

What You’ll Love About Working Here

• Opportunity to work on cutting-edge AI, GenAI, Knowledge Graph, and Digital Twin technologies.
• Exposure to enterprise-scale AI and analytics transformation initiatives.
• Collaborative environment with Data Scientists, AI Engineers, Architects, and domain experts.
• Continuous learning opportunities across Data Engineering, GenAI, MLOps, and Cloud technologies.
• Ability to build scalable AI data foundations that drive measurable business impact and innovation.
• Innovation-driven culture focused on engineering excellence and technical growth.